Conceptual knowledge (or semantic knowledge) refers to our shared knowledge for words, objects, people and emotions. The anterior temporal lobes (ATLs) have been identified as a critical region for the representation of conceptual knowledge through convergent evidence from fMRI in healthy participants, cortical electrode implantation and damage-deficit correlations. With the involvement of the ATLs established, recent research has begun to focus on the functions of subregions of the ATLs - with particular interest surrounding the functions of the left and right ATLs. This thesis investigated three main research questions: (1) What are the functions of the left and right ATLs in semantic representation? (2) How does unilateral damage affect the semantic system and what mechanisms underlie the robustness of the system? (3) Do functional gradations exist within the ATLs? These questions were addressed using convergent methodologies including functional neuroimaging and transcranial magnetic stimulation (TMS) in healthy participants and behavioural and neuroimaging investigations in patients who have undergone unilateral ATL resection. To address the question of left vs. right ATL function, this thesis began by directly comparing the predictions of the different accounts of ATL function in a large-scale meta-analysis of the existing neuroimaging literature (Chapter 2) and in a large sample of patients who had undergone unilateral left or right ATL resection (Chapter 3). The overarching finding was that conceptual knowledge is underpinned by a primarily bilateral ATL system, whereby both the left and right ATLs are critical for normal semantic processing. Secondary to this bilateral representation, relative functional gradations were observed both between and within the ATLs. To address the second research question, Chapter 4 investigated the robustness of the semantic system to unilateral damage, specifically regions involved in the maintenance of conceptual knowledge were localised. Results showed that upregulation occurred within regions previously associated with semantic knowledge. The upregulation of activation after unilateral resection also mimicked the upregulation in control participants during more challenging semantic processing. Chapter 5 examined the behavioural relevance of upregulation in the contralateral ATL after unilateral perturbation using a novel TMS protocol in healthy participants. The findings observed here suggest that the bilateral ATL system is resistant to a degree of unilateral damage/perturbation because semantic representations are distributed between the hemispheres. Therefore, unilateral damage/disruption only results in a mild semantic impairment, as the undamaged/unperturbed hemisphere is available to compensate. Finally, Chapter 6 explored functional gradations within the ATLs by comparing responses in the ventral ATL to different conceptual categories, presented as visual and auditory inputs. The functional gradations observed here are proposed to emerge via differential structural and functional connectivity between the ATLs and sensory-motor and limbic cortices.

To understand how the brain functions, we must investigate the transient interactions that underpin communication between cortical regions. EEG possesses the optimal temporal resolution to capture functional connectivity, but it lacks the spatial resolution to identify the cortical locations responsible. To circumvent this problem electrophysiological connectivity should be investigated at the source level. There are many quantifiers of connectivity applied to EEG data, but some are not sensitive to the direct, or indirect, influence of one region over another, and others require the specification of a priori models so are unsuitable for exploratory analyses. Transfer Entropy (TE) can be used to infer the direction of linear and non-linear information exchange between signals over a range of time-delays within EEG data. This thesis explores the creation of a new method of mapping dynamic brain connectivity using a trial-based TE analysis of EEG source data, and the application of this technique to the investigation of semantic and number processing within the brain. The first paper (Chapter 2) documents the analyses of a semantic category and number magnitude judgement task using traditional ERP techniques. As predicted, the well-known semantic N400 component was found, and localised to left ATL and inferior frontal cortex. An N365 component related to number magnitude judgement was localised to right superior parietal regions including the IPS. These results offer support for the hub-and-spoke model of semantics, and the triple parietal model of number processing. The second paper (Chapter 3) documents an analysis of the same data with the new trial-based TE analysis. Word and number data were analysed at 0-200ms, 200-400ms, and 400-600ms following stimulus presentation. In the earliest window, information exchange was occurring predominately between occipital sources, but by the latest window it had become spread out across the brain. Task-dependent differences of regional information exchange revealed that temporal sources were sending more information to occipital sources following words at 0-200ms. Furthermore, the direction and timing of information movement within a front-temporal-parietal network was identified during 0-400ms of the number magnitude judgment. The final paper (Chapter 4), documents an attempt to track the influence of TMS through the brain using the TE analysis. TMS was applied to bilateral ATL and IPS because they are both important hubs in the brain networks that support semantic and number processing respectively. Left ATL TMS influenced sources located primarily in wide-spread left temporal lobe, and inferior frontal and inferior occipital cortices. The anatomical connectivity profile of the temporal lobe suggests that these are all plausible locations, and they exhibited excellent spatial similarities to the results of neuroimaging experiments that probed semantic knowledge. The analysis of right ATL TMS obtained a mirror image of the left. Left parietal stimulation resulted in a bilateral parietal, superior occipital, and superior prefrontal influence, which extended slightly further in the ipsilateral hemisphere to stimulation site. A result made possible by the short association and callosal fibres that connect these areas. Again, the results at the contralateral site were a virtual mirror image. The thesis concludes with a review of the experimental findings, and a discussion of methodological issues still to be resolved, ideas for extensions to the method, and the broader implications of the method on connectivity research.

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The current thesis addresses some of the unresolved predictions of recent models of the semantic brain system, such as the hub-and-spokes model. In particular, we tackle different aspects of the hypothesis that a widespread network of interacting heteromodal (hub(s)) and unimodal (spokes) cortices underlie semantic cognition. For this purpose, we use connectivity analyses, measures of graph theory and permutation-based statistics with source reconstructed Electro-/MagnetoEncephaloGraphy (EEG/MEG) data in order to track dynamic modulations of activity and connectivity within the semantic networks while a concept unfolds in the brain. Moreover, in order to obtain more accurate connectivity estimates of the semantic networks, we propose novel methods for some of the challenges associated with EEG/MEG connectivity analysis in source space. We utilised data-driven analyses of EEG/MEG recordings of visual word recognition paradigms and found that: 1) Bilateral Anterior Temporal Lobes (ATLs) acted as potential processor hubs for higher-level abstract representation of concepts. This was reflected in modulations of activity by multiple contrasts of semantic variables; 2) ATL and Angular Gyrus (AG) acted as potential integrator hubs for integration of information produced in distributed semantic areas. This was observed using Dynamic Causal Modelling of connectivity among the main left-hemispheric candidate hubs and modulations of functional connectivity of ATL and AG to semantic spokes by word concreteness. Furthermore, examining whole-brain connectomes using measures of graph theory revealed modules in the right ATL and parietal cortex as global hubs; 3) Brain oscillations associated with perception and action in low-level cortices, in particular Alpha and Gamma rhythms, were modulated in response to words with those sensory-motor attributes in the corresponding spokes, shedding light on the mechanism of semantic representations in spokes; 4) Three types of hub-hub, hub-spoke and spoke-spoke connectivity were found to underlie dynamic semantic graphs. Importantly, these results were obtained using novel approaches proposed to address two challenges associated with EEG/MEG connectivity. Firstly, in order to find the most suitable of several connectivity metrics, we utilised principal component analysis (PCA) to find commonalities and differences of those methods when applied to a dataset and identified the most suitable metric based on the maximum explained variance. Secondly, reconstruction of EEG/MEG connectomes using anatomical or fMRI-based parcellations can be significantly contaminated by spurious leakage-induced connections in source space. We, therefore, utilised cross-talk functions in order to optimise the number, size and locations of cortical parcels, obtaining EEG/MEG-adaptive parcellations. In summary, this thesis proposes approaches for optimising EEG/MEG connectivity analyses and applies them to provide the first empirical evidence regarding some of the core predictions of the hub-and-spokes model. The key findings support the general framework of the hub(s)-and-spokes, but also suggest modifications to the model, particularly regarding the definition of semantic hub(s).